Abstract: Provided are a system, method, and storage medium for smart city fire emergency prevention based on an Internet of Things large model. The method includes: determining a plurality of fire risk coefficients of a plurality of preset regions based on a temperature distribution, a crowd distribution, a region type, and historical danger data of the plurality of preset regions; determining a target region based on the plurality of fire risk coefficients and a plurality of risk thresholds; and generating a monitoring instruction including a sampling point and a sampling amount based on a fire risk coefficient of the target region, and sending the monitoring instruction to an emergency supervision object platform through an emergency supervision sensing network platform, to control an unmanned aerial vehicle (UAV) of the emergency supervision object platform to move to the sampling point and acquire monitoring data corresponding to the sampling amount at the sampling point.

Abstract: A method and an IoT large model system for smart city falling object emergency supervision are provided. The method includes: obtaining a surveillance video stream including a building facade; identifying potential falling object(s) and corresponding risk feature label(s) according to the surveillance video stream; determining falling object risk level(s) of the potential falling object(s) according to the potential falling object(s) and the risk feature label(s); determining a regional risk level of each region in the building facade according to the falling object risk level(s); in response to determining that there is a risk area where the regional risk level is greater than a preset risk level, controlling a lighting device corresponding to the risk area to operate with a warning color; and determining early warning information according to the risk feature label(s), and controlling an early warning device corresponding to the risk area to issue the early warning information.

Abstract: Disclosed is a system for urban heat island effect emergency monitoring based on an IoT large model. The system includes an emergency supervision management platform. The emergency supervision management platform is configured to: determine heat island levels of a plurality of candidate nodes; determine one or more target nodes and cooling parameters of one or more target nodes; determine one or more watering vehicles corresponding to the one or more target nodes; send the one or more target nodes to navigation terminals of the one or more watering vehicles corresponding to the one or more target nodes via a wireless network to control the navigation terminals to display navigation routes to the one or more target nodes; and control the one or more watering vehicles and spray systems to perform watering and spraying based on the cooling parameters of the one or more target nodes.

Abstract: Disclosed is an IoT large model system for emergency supervision of low-lying road sections, the system includes an emergency supervision management platform; the emergency supervision management platform is configured to: obtain vehicle operation data of a low-lying area through an emergency supervision object platform; determine waterlogging data based on the vehicle operation data; determine a traffic risk based on the waterlogging data; in response to determining that the traffic risk is greater than a first threshold, determine drainage parameters; determine dispatch parameters based on the drainage parameters; and send, based on the dispatch parameters, a dispatch packet including the drainage parameters to an unmanned vehicle fleet through a heterogeneous communication network, control an unmanned vehicle equipped with a drainage device to travel to the low-lying area, and control a pumping power of the drainage device to be set to a pumping power in the drainage parameters.

Abstract: The present invention provides a method for regulating a flow meter of an industrial and commercial unit of smart gas, an Internet of Things (IoT) system and a medium. The method is implemented by a smart gas management platform of an IoT system for regulating a flow meter of an industrial and commercial unit of smart gas, and comprises: obtaining operation data, a time feature, and user feedback data, the operation data including gas usage data and gas outage feedback data of the industrial and commercial unit; determining, based on the operation data, the time feature, and the user feedback data, a gas flow trend of a low balance user; and determining, based on the gas flow trend, the time feature, and the gas outage feedback data, continuous gas supply parameters of the low balance user, the continuous gas supply parameters including at least one of a continuous gas supply quota and a continuous gas supply time.

Abstract: A method and a system for traffic vehicle emergency management based on an Internet of Things (IoT) large model are provided. The method includes: determining a first anomaly confidence level of each of at least one vehicle; in response to the first anomaly confidence level being greater than a confidence threshold, determining an anomalous vehicle, a second anomaly confidence level of the anomalous vehicle, and an anomaly type of the anomalous vehicle through an anomalous vehicle monitoring model; determining a control type and a control parameter based on the anomalous vehicle, the second anomaly confidence level of the anomalous vehicle, and the anomaly type of the anomalous vehicle; and in response to the control type being anomalous vehicle control, issuing an early warning on a travel route of the anomalous vehicle via the early warning device.

Abstract: Provided is a system for emergency handling of urban storage tanks based on an IoT large model. The system includes an emergency supervision management platform. The emergency supervision management platform is configured to: obtain a tank working state of a storage tank at a first preset time; determine a state change value of the storage tank based on the tank working state; in response to determining that the state change value satisfies a first preset condition, determine an emergency control parameter based on tank monitoring data, wherein the emergency control parameter includes a water mist spraying speed of a cooling device; and control the cooling device to spray water mist toward an outer wall of the storage tank based on the emergency control parameter.

Abstract: Disclosed are a method and an IoT large model system for smart city elevator operation, and a storage medium. The method includes: determining an anomaly feature of a target elevator based on a load and an elevator feature of the target elevator through an anomaly database corresponding to the target elevator; determining an elevator operation risk of the target elevator based on the anomaly feature; determining a passenger posture feature and a passenger distribution feature based on elevator car image data of the target elevator, and determining a passenger behavior risk; determining an out-of-control risk of the target elevator based on the elevator operation risk and the passenger behavior risk; generating an elevator regulation instruction for the target elevator based on the out-of-control risk; and controlling an operation speed of the target elevator based on the elevator regulation instruction.

Abstract: A system and a method for emergency supervision of an open flame area in a smart city based on an IoT large model are provided. The system includes an emergency supervision management platform configured to: determine a first hazardous area based on a gas output flow rate of at least one gas storage tank and a gas usage flow rate of at least one gas device in at least one area; control a UAV to travel to the first hazardous area based on a UAV acquisition command, and acquire a device image sequence; determine, based on the device image sequence, a flame feature through a feature recognition large model; determine an explosion risk of the first hazardous area based on the flame feature and an air flow rate; and determine a valve closure command based on the explosion risk, and close a target valve based on the valve closure command.

Abstract: A gas purification system and method based on an intelligent gas regulatory IoT are provided. The method includes obtaining target detection data and target flow data of a pipeline to be recovered; determining a gas pollution value based on the target detection data and the target flow data; determining at least one candidate purification parameter based on a reference purification parameter; determining, for each of the at least one candidate purification parameter, a purification effect based on the gas pollution value, a total gas volume, and the candidate purification parameter through an effect determination model; determining a purification parameter based on the purification effect of the at least one candidate purification parameter; determining a recovery instruction and sending it to at least one user interaction device via the gas device object platform; in response to obtaining a recovery completion instruction, sending the purification parameter to the gas device object platform.

Abstract: Disclosed is a method for controlling data transmission for smart gas, comprising: obtaining gas data of a gas user, and storing the gas data into a storage unit; predicting a probability of full storage of the storage unit within a preset future time period based on a historical data increment of the storage unit; in response to the probability of full storage meeting a preset probability condition: obtaining the gas data of the gas user within the preset time period; determining the upload demand degree based on the gas data; and in response to the upload demand degree meeting a preset condition, transmitting the gas data within the preset time period to the smart gas management platform based on the smart gas object platform at a target upload time point of at least one smart gas meter of the gas user.

Abstract: The present disclosure provides an Industrial Internet of Things for early warning of descending function fault of equipment, comprising a management platform, wherein the management platform is configured to perform following operations including: obtaining execution status of at least one production task executed by equipment in a preset time period; based on the execution status of the at least one production task, judging whether the equipment has a descending function fault; in response to the equipment having the descending function fault, issuing an early warning and repairing the equipment.

Abstract: The present disclosure relates to a method and system for city lifeline pipeline burst prevention based on an IoT large model. The method includes: obtaining fluid pressure data; determining a pipe burst probability of a pipeline network node based on the fluid pressure data; and determining a target valve and a valve opening degree of the target valve based on the pipe burst probability, and controlling the target valve to the valve opening degree.

Abstract: Disclosed are an IoT system, a method, and a storage medium for generating a sampling parameter for a gas pipeline. The method is executed by a government safety monitoring and management platform, and includes: obtaining pipeline sensing data; determining the sampling parameter based on the pipeline sensing data; and in response to obtaining at least one piece of sampling data from at least one sampling device, determining a fault detection command based on the sampling data, and sending the fault detection command to a gas maintenance object platform to schedule a manual inspection. The IoT system includes the government safety monitoring and management platform, a government safety monitoring sensing network platform, a government safety monitoring object platform, a gas company sensing network platform, a gas equipment object platform, and the gas maintenance object platform. The method may be executed by reading computer instructions stored in a non-transitory computer-readable storage medium.

Abstract: A system for emergency prevention and control for urban lifeline gas pipelines during flooding based on a large model is provided. The system includes an emergency supervision-management platform configured to: construct a gas pipeline network map based on pipeline pressures and gas flow rates of a plurality of pipeline nodes; determine a plurality of suspected leakage points and a plurality of leakage confidence levels of the plurality of suspected leakage points; perform an evaluating process on each suspected leakage point; determine, based on a plurality of corrosion risks and a plurality of deformation risks of the plurality of suspected leakage points, a comprehensive risk of a target pipeline node using a prediction model; and in response to the comprehensive risk meeting a drainage condition, automatically send a control signal to a drainage robot to drive the drainage robot to carry out drainage.

Abstract: An intelligent manufacturing industrial Internet of Things with a front split service platform for calibrating a binocular camera is provided, which includes: an obtaining module configured to obtain an image taken by a first camera on a production line as a first image data and an image taken by a second camera as a second image data through a sensor network platform; a three-dimensional module configured to process into three-dimensional image data; a recognition module configured to obtain a plurality of point positions of a distortion part as judgment point positions; a mapping module configured to map the judgment point positions to the second image data to form second calibration point positions; and a calibration module configured to calibrate the first camera and the second camera according to first calibration point positions and the second calibration point positions.

Abstract: A gas recovery system and method based on an intelligent gas regulatory IoT are provided. The system includes a government regulatory management platform, a government regulatory sensor network platform, a government regulatory object platform including a gas company management platform, a gas company sensor network platform, and a gas device object platform. The method includes obtaining target detection data and target flow data of a pipeline to be recovered from the gas device object platform; determining a gas pollution value based on the target detection data and the target flow data; determining a purification parameter of a purification device based on the gas pollution value and the target flow data; determining a recovery instruction and sending it to at least one user interaction device via the gas device object platform; in response to obtaining a recovery completion instruction, sending the purification parameter to the gas device object platform.

Abstract: Provided is a system and a method for suburban gas pipeline emergency supervision used in an urban lifeline project, the system includes an emergency supervision and management platform and an emergency supervision object platform, and the emergency supervision and management platform is configured to: in response to completion of a remote regulation operation of a target gas pipeline, obtain a first information sequence; determine a first regulation feature based on the first information sequence and a remote regulation parameter of the remote regulation operation; determine failure probability of the remote regulation operation based on the first regulation feature; in response to the failure probability satisfying a predetermined failure condition, determine a failure cause distribution; determine a failure cause and send a control signal to the emergency supervision object platform for executing a regulation strategy based on the failure cause distribution.

Abstract: Provided is a method and an Internet of Things (IoT) system for pipeline repair. The method includes: obtaining pipeline repair equipment information and pipeline data to be repaired; determining a performance level of a pipeline repair equipment based on the pipeline repair equipment information; determining a target pipeline repair equipment based on the performance level; constructing a pipeline map to be repaired; determining a repair urgency for each pipeline to be repaired; determining at least one target repair pipeline; determining a pipeline repair sequence; determining repair commands based on the pipeline repair sequence; and controlling, based on the repair commands, the target pipeline repair equipment that is in an idle state and has the performance level not less than a performance threshold to prioritize processing a target repair pipeline with the repair urgency not less than an urgency threshold.

Abstract: The embodiments of the present disclosure provide methods and systems for scheduling operation and maintenance personnel based on an Internet of Things (IoT) system for smart gas installation management. The method may include: obtaining user installation information of at least one operation and maintenance area; determining target installation information of the at least one operation and maintenance area; determining a door-to-door service plan for the at least one operation and maintenance area; obtaining collection data of a gas device configured in the operation and maintenance area; determining a count of on-call personnel of the at least one operation and maintenance area; determining a scheduling capability value of the at least one operation and maintenance area; determining a real-time scheduling instruction; and in response to compensation time off information, updating the scheduling capability value, and adjusting the real-time scheduling instruction.